Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "106"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 106 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 24 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 24 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 106, Node N09:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460007 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.089475 -0.672478 -0.616004 -0.057902 -0.190517 -0.457425 -0.029274 -0.224353 0.6344 0.6430 0.3290 nan nan
2459999 digital_ok 0.00% 89.14% 85.71% 0.00% - - nan nan nan nan nan nan nan nan 0.1192 0.1201 0.0470 nan nan
2459998 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.199440 -0.733394 -0.550736 -0.154324 0.123397 -0.836290 0.698533 -0.421649 0.6290 0.6358 0.3612 nan nan
2459997 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.019495 -0.751731 -0.555973 -0.011026 -0.587737 -1.049528 0.859432 -0.419632 0.6368 0.6485 0.3632 nan nan
2459996 digital_ok 100.00% 99.19% 99.35% 0.00% - - 213.631928 214.003726 inf inf 3301.390585 3273.349303 5251.460507 5121.988186 0.5543 0.3806 0.4222 nan nan
2459995 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.038536 -0.848155 -0.457695 -0.155906 3.440197 -0.475089 0.368006 0.374433 0.6276 0.6393 0.3603 nan nan
2459994 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.329089 -0.931101 -0.760854 -0.110143 0.226578 -0.724195 0.133172 0.247039 0.6242 0.6318 0.3604 nan nan
2459993 digital_ok 0.00% 0.00% 0.00% 0.00% - - 0.983717 -1.148294 -1.023180 -0.295389 1.313700 -0.294846 0.094175 0.226456 0.6184 0.6370 0.3706 nan nan
2459991 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.604688 -1.125989 -0.953292 -0.305329 1.228511 -0.796602 -0.128321 0.187060 0.6429 0.6421 0.3665 nan nan
2459990 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.500515 -0.764107 -1.067406 -0.448586 0.095999 -0.826044 -0.305024 -0.609106 0.6409 0.6414 0.3643 nan nan
2459989 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.731274 -0.781381 -0.964555 -0.178279 0.013693 -1.221341 -0.254215 -0.669038 0.6328 0.6368 0.3656 nan nan
2459988 digital_ok 100.00% 0.00% 0.00% 0.00% - - 1.481228 -0.989428 0.955757 -0.581229 9.066586 -0.804173 107.980645 0.043321 0.6208 0.6365 0.3544 nan nan
2459987 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.753445 -1.057753 -1.128223 -0.242636 -0.576957 -0.968465 -0.213919 -0.271779 0.6449 0.6450 0.3542 nan nan
2459986 digital_ok 0.00% 0.00% 0.00% 0.00% - - 2.096123 -0.958285 -1.208726 -0.434511 0.036747 -0.701821 -0.679703 -1.224673 0.6651 0.6699 0.3116 nan nan
2459985 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.982934 -0.598634 -0.985816 -0.209860 -0.318370 -1.019736 -0.225815 0.360551 0.6435 0.6407 0.3622 nan nan
2459984 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.826522 -0.396639 -0.811482 -0.111283 -0.815890 -1.122809 -0.588350 -0.643365 0.6590 0.6558 0.3392 nan nan
2459983 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.770774 1.567681 -1.123854 -0.405052 -0.212715 -0.987398 -0.633711 -0.950654 0.6731 0.6934 0.3036 nan nan
2459982 digital_ok 0.00% 0.00% 0.00% 0.00% - - 2.717498 1.337218 -0.909628 -0.171066 -0.847621 -0.697468 -0.652768 -0.436114 0.7266 0.7284 0.2644 nan nan
2459981 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.544815 1.248752 -1.413678 -0.661554 0.492955 -1.036153 -0.417857 0.227866 0.6459 0.6573 0.3597 nan nan
2459980 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.604784 1.234423 -1.311335 -0.423219 -0.678128 -1.300376 -1.154281 -0.754395 0.6906 0.7013 0.2849 nan nan
2459979 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.531807 1.232865 -1.440125 -0.561788 -0.140263 -1.151958 -0.285026 -0.250284 0.6394 0.6546 0.3619 nan nan
2459978 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.569047 1.257591 -1.474103 -0.631182 0.081864 -0.999965 -0.312512 -0.106492 0.6394 0.6534 0.3673 nan nan
2459977 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.553081 1.372974 -1.303842 -0.440925 0.625245 -0.970650 -0.127938 0.272051 0.6070 0.6225 0.3348 nan nan
2459976 digital_ok 0.00% 0.00% 0.00% 0.00% - - 1.550789 1.330441 -1.421865 -0.560572 1.481922 -0.394799 -0.364277 -0.408423 0.6456 0.6585 0.3567 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 106: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.089475 1.089475 -0.672478 -0.616004 -0.057902 -0.190517 -0.457425 -0.029274 -0.224353

Antenna 106: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 106: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.199440 1.199440 -0.733394 -0.550736 -0.154324 0.123397 -0.836290 0.698533 -0.421649

Antenna 106: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.019495 1.019495 -0.751731 -0.555973 -0.011026 -0.587737 -1.049528 0.859432 -0.419632

Antenna 106: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Power inf 213.631928 214.003726 inf inf 3301.390585 3273.349303 5251.460507 5121.988186

Antenna 106: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Temporal Variability 3.440197 1.038536 -0.848155 -0.457695 -0.155906 3.440197 -0.475089 0.368006 0.374433

Antenna 106: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.329089 1.329089 -0.931101 -0.760854 -0.110143 0.226578 -0.724195 0.133172 0.247039

Antenna 106: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Temporal Variability 1.313700 0.983717 -1.148294 -1.023180 -0.295389 1.313700 -0.294846 0.094175 0.226456

Antenna 106: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.604688 1.604688 -1.125989 -0.953292 -0.305329 1.228511 -0.796602 -0.128321 0.187060

Antenna 106: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.500515 -0.764107 1.500515 -0.448586 -1.067406 -0.826044 0.095999 -0.609106 -0.305024

Antenna 106: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.731274 -0.781381 1.731274 -0.178279 -0.964555 -1.221341 0.013693 -0.669038 -0.254215

Antenna 106: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Temporal Discontinuties 107.980645 -0.989428 1.481228 -0.581229 0.955757 -0.804173 9.066586 0.043321 107.980645

Antenna 106: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.753445 1.753445 -1.057753 -1.128223 -0.242636 -0.576957 -0.968465 -0.213919 -0.271779

Antenna 106: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 2.096123 -0.958285 2.096123 -0.434511 -1.208726 -0.701821 0.036747 -1.224673 -0.679703

Antenna 106: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.982934 -0.598634 1.982934 -0.209860 -0.985816 -1.019736 -0.318370 0.360551 -0.225815

Antenna 106: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.826522 1.826522 -0.396639 -0.811482 -0.111283 -0.815890 -1.122809 -0.588350 -0.643365

Antenna 106: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.770774 1.770774 1.567681 -1.123854 -0.405052 -0.212715 -0.987398 -0.633711 -0.950654

Antenna 106: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 2.717498 2.717498 1.337218 -0.909628 -0.171066 -0.847621 -0.697468 -0.652768 -0.436114

Antenna 106: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.544815 1.248752 1.544815 -0.661554 -1.413678 -1.036153 0.492955 0.227866 -0.417857

Antenna 106: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.604784 1.234423 1.604784 -0.423219 -1.311335 -1.300376 -0.678128 -0.754395 -1.154281

Antenna 106: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.531807 1.531807 1.232865 -1.440125 -0.561788 -0.140263 -1.151958 -0.285026 -0.250284

Antenna 106: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.569047 1.257591 1.569047 -0.631182 -1.474103 -0.999965 0.081864 -0.106492 -0.312512

Antenna 106: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.553081 1.553081 1.372974 -1.303842 -0.440925 0.625245 -0.970650 -0.127938 0.272051

Antenna 106: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
106 N09 digital_ok ee Shape 1.550789 1.330441 1.550789 -0.560572 -1.421865 -0.394799 1.481922 -0.408423 -0.364277
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